darija_test
This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6520
- Accuracy: 0.7041
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.813 | 1.0 | 169 | 0.7390 | 0.2959 |
| 0.9437 | 2.0 | 338 | 0.6520 | 0.7041 |
| 0.759 | 3.0 | 507 | 0.6080 | 0.7041 |
| 0.7936 | 4.0 | 676 | 0.6582 | 0.7041 |
| 0.8051 | 5.0 | 845 | 0.6452 | 0.7041 |
| 0.7397 | 6.0 | 1014 | 0.6422 | 0.7041 |
| 0.5792 | 7.0 | 1183 | 0.6132 | 0.7041 |
| 0.5339 | 8.0 | 1352 | 0.6095 | 0.7041 |
| 0.5152 | 9.0 | 1521 | 0.6136 | 0.7041 |
| 0.4909 | 10.0 | 1690 | 0.6181 | 0.7041 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
SI2M-Lab/DarijaBERT